VC
Me parecio super enriquecedor el contenido del curso.
Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow. By the end of the course, learners will have the necessary skills to write Python scripts for automating common MLOps tasks. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their Python skills.
VC
Me parecio super enriquecedor el contenido del curso.
XH
This course was great and highly applicable to my work. The content was relevant, well-structured, and provided practical skills that I can directly use in my job.
AA
One of the best of the best courses out there for beginner's friendly to MLOps!
KC
The Courser covered a lot of things with keeping the number of videos low, but python environments in some of the labs were not already created.
MB
One of the best Python courses that I had done, my background is in Data Science not in Engineering. I think that is an advance course since a vast number of concepts are well explained so quickly.
ND
Great learning resources, concise presentations, and clear explanations of all topics
RR
Course content is good, some places gave another perspective to understand the existing approaches.
HH
Python best practices across development, testing & wrapping using API was well covered. Lectures on Python API frameworks can be more in detail.
JR
The course gives you a good direction. But sometimes is complicated to get in the flow, let's say. The teacher has great intention, but he gets lost sometimes.
GS
I liked the opportunity to practice and experiment and challenge questions
OC
A good course suggested for junior engineers and data scientist
AS
Some more advanced Python (Flask, FastAPI, Azure, etc.) could have been explained in more depth and detail with practical labs.